Converting adjacency table into seminr measurement model

Question

I have this adjacency table which we can call df. I want to find a programmatic way to take this table and convert it for use in the seminr package.

#Example of my data 

df <- read.table(text = "  from  to column_position
1     a  V7              11
2     b  V7              15
3     c  V7              10
4     a  V7               9
5     b  V7              12
6     c V16              17
7     a V16               5
8     b V16              27
9     c V16               6
10    a V16              20
11    b V16              14
12    c V16               7
13    a V14              19
14    b V14              18
15    c V20              24
16    a  C5              21
17    b  C5              28
18    c C13              22
19    a C13              23
20    b C16              26
21    c C16              16
22    a C16              25
23    b C15               8
24    c C15              13", header = TRUE)

Typically in seminr you would specific the measurement model in a way like the below:

library(seminr)

  mobi_mm <- constructs(
    reflective("Image",        multi_items("IMAG", 1:5)),
    reflective("Expectation",  multi_items("CUEX", 1:3)),
    reflective("Quality",      multi_items("PERQ", 1:7)),
    reflective("Value",        multi_items("PERV", 1:2)),
    reflective("Satisfaction", multi_items("CUSA", 1:3)),
    reflective("Complaints",   single_item("CUSCO")),
    reflective("Loyalty",      multi_items("CUSL", 1:3))
  )

The output I am expecting to have my table converted in this format:

  mobi_mm <- constructs(
    reflective("V7",        multi_items(item_numbers = c(9,10,11,12,15)),
    ...

  )

I'd imagine some do.call can be used but not entirely sure how exactly I would do so in this specific example.